Traffic congestion in urban road networks is a substantial problem, resulting in significant costs for drivers through wasted time and fuel, detrimental impact to the environment due to increased vehicle emissions, and increased needs for infrastructure upgrades. Poorly timed traffic signals are one of the largest recurring sources of traffic congestion. Even when signals have been recently retimed, the inability to respond to current traffic patterns can cause pockets of congestion that lead to larger traffic jams. Inefficiencies in traffic signal timing stem from poor allocation of green time, inability to respond to real-time conditions, and poor coordination between adjacent intersections.
Operation of the traffic signals at a given intersection is typically governed by a signal timing plan. A timing plan assumes that compatible vehicle movement paths through the intersection (e.g., north and south lanes) have been grouped into movement phases. It specifies the sequence in which phases should be activated (turned green) and the duration of each green phase. The duration of each phase is subject to minimum and maximum constraints to ensure fairness and the transition from one phase to the next must obey safety constraints (fixed-length yellow and all red periods). A timing plan is graphically depicted in FIG. 1.
Conventional signal systems use pre-programmed timing plans to control traffic signal operation. Fixed timings allocate fixed cycle lengths and green splits, while actuated signals use vehicle detectors to allow simple, minor variations in phase durations within the constraints of the timing plan (e.g., the green may be indefinitely allocated to the dominant traffic flow, only shifting to a cross street phase when a waiting vehicle is detected). For coordinated plans, lights often operate in a common cycle length, and offsets are set for coordinated phases between neighbors, on pre-defined corridors. Different timing plans may be invoked at different periods of the day (e.g., during rush and off-peak periods), and the timing plans can impose additional constraints to coordinate the actions of signals at different intersections. The crucial distinction is that timing and coordination plans are computed off-line, based on expected traffic conditions. Adaptive signal systems, in contrast, sense the actual traffic flows approaching intersections and continually adjust intersection timing plans to match current conditions.
The design of adaptive signal systems has received considerable attention over the years, and it is generally recognized that traffic signal improvements offer the biggest payoff for reducing congestion and increasing the effective capacity of existing road networks, and that adaptive traffic signal control systems hold the most promise for improvement. With respect to the control of traffic signal networks, most practical success has been achieved using more centralized approaches (e.g., SCATS, SCOOT, ACS-Lite) that adjust the three fundamental parameters, cycle length, phase split, and offset, for traffic lights. Due to the rather strong restriction imposed on parametric adjustments, these systems are designed to effect changes to traffic signal timings on the order of minutes based on average flow predictions, which limits how quickly and effectively a system can respond to locally changing traffic patterns. Furthermore, centralized coordination can be also susceptible to scalability issues. For example, the network offset adjustment in ACS-Lite has been found to be intractable in real time for only 12 intersections.
To achieve greater real-time responsiveness, other work has focused on techniques for computing intersection timing plans that optimize actual traffic flows (e.g., ALLONS-D, PRODYN, OPAC, RHODES, CRONOS, and others). This class of online planning approaches, sometimes referred to as model-based optimization, often significant tradeoffs have to be made to achieve computational tractability for real-time operation in realistic planning horizons, due to the inefficiency of searching in an exponential planning search space. For these systems, decentralized operations are often not effective in road networks due to the lack of capability to work in sufficiently long horizons and to handle local mis-coordination situations. Rather, these systems are often supported using centralized and hierarchical forms of network flow control, e.g., the coordination and synchronization layers for OPAC in RT-TRACS and REALBAND for the intersection control algorithm COP in RHODES.